Implementation of Coupled Skin Temperature. Atmospheric Data Assimilation System. Jon D. Radakovich, Michael G. Bosilovich,

Similar documents
STUDIES ON MODEL PREDICTABILITY IN VARIOUS CLIMATIC CONDITIONS: AN EFFORT USING CEOP EOP1 DATASET

Evaluation of a New Land Surface Model for JMA-GSM

Evaluating Parametrizations using CEOP

Land Data Assimilation at NCEP NLDAS Project Overview, ECMWF HEPEX 2004

The Choice of Variable for Atmospheric Moisture Analysis DEE AND DA SILVA. Liz Satterfield AOSC 615

Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models

SENSITIVITY OF THE SURFEX LAND SURFACE MODEL TO FORCING SETTINGS IN URBAN CLIMATE MODELLING

P1.34 MULTISEASONALVALIDATION OF GOES-BASED INSOLATION ESTIMATES. Jason A. Otkin*, Martha C. Anderson*, and John R. Mecikalski #

ASSESSMENT AND APPLICATIONS OF MISR WINDS

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. D16, 8618, doi: /2002jd003127, 2003

C. Jimenez, C. Prigent, F. Aires, S. Ermida. Estellus, Paris, France Observatoire de Paris, France IPMA, Lisbon, Portugal

Skin SST assimilation using GEOS Atmospheric Data Assimilation System

The Fate of Saharan Dust Across the Atlantic and Implications for a Central American Dust Barrier

Assimilating Earth System Observations at NASA: MERRA and Beyond

Enhancing Weather Forecasts via Assimilating SMAP Soil Moisture and NRT GVF

GLOBAL LAND DATA ASSIMILATION SYSTEM (GLDAS) PRODUCTS FROM NASA HYDROLOGY DATA AND INFORMATION SERVICES CENTER (HDISC) INTRODUCTION

Interaction of North American Land Data Assimilation System and National Soil Moisture Network: Soil Products and Beyond

Comparison of Convection Characteristics at the Tropical Western Pacific Darwin Site Between Observation and Global Climate Models Simulations

Atmospheric Boundary Layer over Land, Ocean, and Ice. Xubin Zeng, Michael Brunke, Josh Welty, Patrick Broxton University of Arizona

Introducing inland water bodies and coastal areas in ECMWF forecasting system:

Matteo Giorcelli 1,2, Massimo Milelli 2. University of Torino, 2 ARPA Piemonte. Eretria, 08/09/2014

The Community Noah LSM with Multi-physics Options

Global Urban-Scale Land-Atmosphere Modeling with the Land Information System

5. General Circulation Models

Near-surface weather prediction and surface data assimilation: challenges, development, and potential data needs

Addressing Diurnal Temperature Biases in the WRF Model

Intercomparison of Water and Energy Budgets for Five Mississippi Sub-basins between. ECMWF Reanalysis (ERA-40) and NASA-DAO fvgcm for

ERA-CLIM: Developing reanalyses of the coupled climate system

Regional dry-season climate changes due to three decades of Amazonian deforestation

Comparison of NASA AIRS and MODIS Land Surface Temperature and Infrared Emissivity Measurements from the EOS AQUA platform

IMPACT EXPERIMENTS ON GMAO DATA ASSIMILATION AND FORECAST SYSTEMS WITH MODIS WINDS DURING MOWSAP. Lars Peter Riishojgaard and Yanqiu Zhu

ASSESSMENT OF ENERGY BUDGET IN WEATHER FORECASTING GENERAL CIRCULATION MODELS

NASA/NOAA s Global Land Data Assimilation System (GLDAS): Recent Results and Future Plans

CHAPTER 8 NUMERICAL SIMULATIONS OF THE ITCZ OVER THE INDIAN OCEAN AND INDONESIA DURING A NORMAL YEAR AND DURING AN ENSO YEAR

Current status of lake modelling and initialisation at ECMWF

The Fifth-Generation NCAR / Penn State Mesoscale Model (MM5) Mark Decker Feiqin Xie ATMO 595E November 23, 2004 Department of Atmospheric Science

Regional offline land surface simulations over eastern Canada using CLASS. Diana Verseghy Climate Research Division Environment Canada

Effects of sub-grid variability of precipitation and canopy water storage on climate model simulations of water cycle in Europe

GMAO Analyses and Forecasts for YOTC

Land Data Assimilation for operational weather forecasting

4.4 EVALUATION OF AN IMPROVED CONVECTION TRIGGERING MECHANISM IN THE NCAR COMMUNITY ATMOSPHERE MODEL CAM2 UNDER CAPT FRAMEWORK

Atmosphere-Land coupling in the ECMWF model Anton Beljaars European Centre for Medium-range Weather Forecasts (ECMWF) (Reading, UK)

Impact of Eurasian spring snow decrement on East Asian summer precipitation

Land data assimilation in the NASA GEOS-5 system: Status and challenges

Related Improvements. A DFS Application. Mark A. Bourassa

A SATELLITE LAND DATA ASSIMILATION SYTEM COUPLED WITH A MESOSCALE MODEL: TOWARDS IMPROVING NUMERICAL WEATHER PREDICTION

The difficult art of evaluation clouds and convection representation in GCM s

Ice Surface temperatures, status and utility. Jacob Høyer, Gorm Dybkjær, Rasmus Tonboe and Eva Howe Center for Ocean and Ice, DMI

Observational validation of an extended mosaic technique for capturing subgrid scale heterogeneity in a GCM

RAL Advances in Land Surface Modeling Part I. Andrea Hahmann

GKSS. The Inter-Continental Transferability Study. as part of CEOP/GEWEX FORSCHUNGSZENTRUM PAGE

11 days (00, 12 UTC) 132 hours (06, 18 UTC) One unperturbed control forecast and 26 perturbed ensemble members. --

Saharan Dust Induced Radiation-Cloud-Precipitation-Dynamics Interactions

Reconciling leaf physiological traits and canopy-scale flux data: Use of the TRY and FLUXNET databases in the Community Land Model

Investigating the urban climate characteristics of two Hungarian cities with SURFEX/TEB land surface model

Representing inland water bodies and coastal areas in global numerical weather prediction

The MODIS Cloud Data Record

Regional climate modelling in the future. Ralf Döscher, SMHI, Sweden

INVESTIGATING THE SIMULATIONS OF HYDROLOGICAL and ENERGY CYCLES OF IPCC GCMS OVER THE CONGO AND UPPER BLUE NILE BASINS

Objec4ves for this mee4ng

9.4. The newly released 5-year Terra-based monthly CERES radiative flux and cloud product. David R. Doelling, D. F. Keyes AS&M, Inc.

On Surface fluxes and Clouds/Precipitation in the Tropical Eastern Atlantic

Convection Permitting Simulation of Extreme Precipitation Events Lessons Learned

Climate Modeling: From the global to the regional scale

An Intercomparison of Single-Column Model Simulations of Summertime Midlatitude Continental Convection

Assimilation Experiments of One-dimensional Variational Analyses with GPS/MET Refractivity

P1.1 THE QUALITY OF HORIZONTAL ADVECTIVE TENDENCIES IN ATMOSPHERIC MODELS FOR THE 3 RD GABLS SCM INTERCOMPARISON CASE

May 3, :41 AOGS - AS 9in x 6in b951-v16-ch13 LAND SURFACE ENERGY BUDGET OVER THE TIBETAN PLATEAU BASED ON SATELLITE REMOTE SENSING DATA

SATELLITE BASED ASSESSMENT OF THE NSRDB SITE IRRADIANCES AND TIME SERIES FROM NASA AND SUNY/ALBANY ALGORITHMS

GABLS4 Results from NCEP Single Column Model

Air sea satellite flux datasets and what they do (and don't) tell us about the air sea interface in the Southern Ocean

Xianglei Huang University of Michigan Xiuhong Chen & Mark Flanner (Univ. of Michigan), Ping Yang (Texas A&M), Dan Feldman and Chiancy Kuo (LBL, DoE)

Asymmetric response of maximum and minimum temperatures to soil emissivity change over the Northern African Sahel in a GCM

Terrestrial Snow Cover: Properties, Trends, and Feedbacks. Chris Derksen Climate Research Division, ECCC

Evaluation of a MODIS Triangle-based Algorithm for Improving ET Estimates in the Northern Sierra Nevada Mountain Range

Lake parameters climatology for cold start runs (lake initialization) in the ECMWF forecast system

Assimilation of satellite derived soil moisture for weather forecasting

Land surface precipitation and hydrology in MERRA-2

A Study of the Relations between Soil Moisture, Soil Temperatures and Surface Temperatures Using ARM Observations and Offline CLM4 Simulations

1. Current atmospheric DA systems 2. Coupling surface/atmospheric DA 3. Trends & ideas

Atmospheric Sciences 321. Science of Climate. Lecture 13: Surface Energy Balance Chapter 4

An Introduction to Climate Modeling

Meteo-France operational land surface analysis for NWP: current status and perspectives

July November 2011 Highlights

An Ensemble Land Surface Modeling and Assimilation Testbed for HEPEX

Claude Duguay University of Waterloo

GFAS Methodology & Results

Sensitivity to the PBL and convective schemes in forecasts with CAM along the Pacific Cross-section

METRIC tm. Mapping Evapotranspiration at high Resolution with Internalized Calibration. Shifa Dinesh

Implementation of Land Information System in the NCEP Operational Climate Forecast System CFSv2. Jesse Meng, Michael Ek, Rongqian Yang, Helin Wei

Lecture 10. Surface Energy Balance (Garratt )

Turbulent fluxes. Sensible heat flux. Momentum flux = Wind stress ρc D (U-U s ) 2. Latent heat flux. ρc p C H (U-U s ) (T s -T a )

The SeaFlux Turbulent Flux Dataset Version 1.0 Documentation

EVALUATING SOLAR RESOURCE VARIABILITY FROM SATELLITE AND GROUND-BASED OBSERVATIONS

Influence of variations in low-level moisture and soil moisture on the organization of summer convective systems in the US Midwest

Regional Climate Simulations with WRF Model

Remote Sensing Applications for Land/Atmosphere: Earth Radiation Balance

Diagnosis of the summertime warm and dry bias over the U.S. Southern Great Plains in the GFDL climate model using a weather forecasting approach

High-resolution simulations of the Urban Heat Island

Interactions between Vegetation and Climate: Radiative and Physiological Effects of Doubled Atmospheric CO 2

Transcription:

Implementation of Coupled Skin Temperature Implementation Analysis and of Bias Coupled Correction Skin Temperature in a Global Analysis Atmospheric and Bias Data Correction Assimilation in a System Global Atmospheric Data Assimilation System Jon D. Radakovich, Michael G. Bosilovich, Michael Jiun-dar G. Chern Bosilovich, and Arlindo Jon D. da Radakovich, Silva Jiun-dar Chern, Arlindo da Silva and Francis Verter Global Modeling and Assimilation Office Global NASA Modeling Goddard and Space Assimilation Flight Center Office NASA Greenbelt, Goddard Space MD 20771 Flight Center

Motivation: Introduction surface skin temperature (Ts) is a critical state because it reflects the surface radiative properties and energy budget and can dictate convective initiation. Reliable Ts field from the operational GMAO DAS (Global Modeling and Assimilation Office Data Assimilation System) is a key requirement from scientific instrument team users. Method: integration of the state-of-the-art NCAR Community Land Model (CLM) version 2.0 land-surface model (Dai et al. 2002; Zeng et al. 2002; Bonan et al. 2002) into GEOS4. Ts analysis and coupled bias correction

Models & Assimilation System The Finite-Volume GCM (fvgcm) Capable of resolving atmospheric motions from meso- to planetary-scale with a terrain-following Lagrangian controlvolume vertical coordinate system (Lin and Rood 1999). NCAR CAM2 physical parameterizations The Goddard Earth Observing System (GEOS4) The fvdas first utilizes a Statistical Quality Control (SQC) system to screen the observational data. The analysis is then performed by the Physical-Space Statistical Analysis System (PSAS; Cohn et al. 1998).

Models & Assimilation System The Community Land Model (CLM v2) One-dimensional point model that uses sub-grid scale tiles. One vegetation layer with a photosynthesis-conductance model to realistically depict evapotranspiration (Bonan 1996). 10-uneven vertical soil layers with water, ice, and temperature states in each layer. Up to five snow layers depending on the snow depth with water flow, refreezing, compaction and aging allowed. Utilizes two-stream canopy radiative transfer, the Bonan lake model (1996), topographic enhanced streamflow based on TOPMODEL (Beven and Kirkby 1979), and turbulence is considered above, within, and below the canopy.

Skin Temperature Assimilation and Coupled Bias Correction Incremental Bias Correction (Daily): A variant of the Dee and da Silva (1998) BC scheme was implemented where, a running estimate of the bias is calculated based on Ts observations and added to the energy balance at every timestep to counteract the subsequent forcing of the analyzed Ts back to the initial state. δw w b k a f a = = w = K ( w b f f k 1 o b Hw f k 1 γ δw f + δw a + a b f ) f = b f b τ f b was added to the energy balance for the canopy and for the top layer soil/snow surface, and then updated at the analysis times.

Skin Temperature Assimilation and Coupled Bias Correction Diurnal Bias Correction (Diurnal, DBC) IBC removed the time mean bias, but not the bias in the mean diurnal cycle thus DBC was implemented. Time-dependent bias modeled with a sine wave parameterization: b f ( t) = ( a cosω t + b sinω ) a = a γδw a cosω t b = b γδw a sinω t 2π where ω 1 = is the diurnal harmonic 24h

Summary of Experiments Coupled Ts technique was tested in the fvdas CLM2 framework and run at 1 x 1.25 horizontal resolution with 55 vertical levels from May through September 2001. The atmospheric analysis is performed every 6 hours, while the Ts analysis is done every 3 hours. The bias estimate is updated at the analysis time. ISCCP (International Satellite Cloud Climatology Proect; Rossow and Schiffer, 1991) 3-hourly Ts observations were used for the surface analysis and BC.

Summary of Experiments Control (CTL) July-September 2001 Daily Bias Correction (EXP1) Includes a single bias at each grid point Diurnal Bias Correction (EXP2) Includes 3 hourly (8) biases at each grid point ANA Analysis cycle BKG Background (model) CTL-AI, EXP1-AI, EXP2-AI add the analysis increment into the surface energy budget

Analysis and Bias Correction 320 Analysis and Bias Correction 315 310 Ts(K) 305 300 295 290 0 3 6 9 12 15 18 21 24 Hour CTL CTL-AI EXP2 EXP2-AI ISCCP The analysis increments immediate impact, not long lasting, bias correction is applied at every time step

Analysis Skin Temperature Differences (July 2001Day and Night) Analysis compared back to ISCCP Daily bias corrections remove of many of the regional biases Diurnal bias corrections address most bias

Background Skin Temperature Differences (July 2001 Day and Night) Most improvement in skin temperature occurs with daily bias correction Only slight improvement in global bias, some improvement in regions

July 2001 T2m Station Observation Differences & Improvement

July 2001 T2m Station Observation Amplitude Differences & Improvement Amplitude of the monthly mean diurnal cycle The daily bias correction has little or negative affect on amplitude The diurnal bias correction makes a positive impact for many of the largest biases

July 2001 T2m Station Observation Amplitude Differences & Improvement Most regions are improved, though to varying degrees Eastern Europe is a region where the diurnal amplitude is not improved by diurnal bias correction Daily correction seems to improve the amplitude in Eastern Europe

Fluxes & Soil Moisture

EOP-1 July Sept, 2001 Reference Sites mostly in GEWEX CSEs 40 stations in total 8 with complete energy/radiation observations (Circled) CEOP In-situ Observations

CEOP July 2001 In-situ mean Biases Station Q2m T2m Ts Rn Hs LE Hg Rsd Rsu Rld Rlu B BALTEX Cabauw -1.94 3.10 24.3 59.7-48.0 62.7 7.8-18.8 14.8-47.9 BALTEX Lindenberg -0.56 0.14 45.9 34.9-14.6 0.9 52.6 10.7-5.8-0.9-41.2 MAGS BERMS -1.38 0.31 5.5 8.1-25.6 6.0 39.3 19.5-2.1 12.1-31.4 LBA Manaus -0.91-1.15 2.8-2.3-14.3 3.0 8.4-4.5-4.6-17.4 LBA Rondonia -1.99 0.31-0.74 2.9 5.6 4.5 25.8 9.3-20.4-6.0-33.2 GAPP Bondville -1.05 1.88 1.65 30.1 13.7-17.9-1.2 18.0-1.4 11.1 20.4-30.2 GAPP Ft_Peck -1.75-1.26-4.05 25.8 19.9-4.6 28.9 15.0 13.5-13.2-2.9 GAPP ARMSGP (E15) 1.76-1.32-2.68 30.5 8.9 37.2 2.4 11.4-13.7-10.6-16.6 4.0 ARM NSA Atqasuk -0.73-1.15-0.94 15.8-40.4 ARM NSA Barrow 0.37 4.42 2.07-30.5-40.4 CAMP Mongolia (230) -0.24 0.41-0.31 18.2 8.2 g/kg K W m -2 Mean biases of the diurnal bias correction Redshows improvement of the mean bias (Blue shows degradation)

July 2001 CEOP Comparisons CTL LBA Rondonia Site (-10.08, -61.93º) Observations are dotted lines Improvement in the sensible & latent heat flux due to the DBC EXP2 Significant reduction in the daytime warm bias in the skin temperature and 2 m temperature with inclusion of DBC. Ground heat flux is the residual from the energy balance and thus includes the energy flux from the bias term.

July 2001 CEOP Comparisons CTL GAPP Bondville Site (40.01, -88.29º) Observations are dotted lines Slight improvement shown in the sensible heat flux, but not the latent heat flux. EXP2 With reduced sensible heat there is a compensating increase in the residual ground heat flux, but this is likely attributable to the bias flux which was not removed from the residual. Only small improvement in the TSKIN and T2m resulting from the DBC.

Conclusions Preliminary results show that the coupled skin temperature assimilation and bias correction was for the most part a success The analysis closely draws to the observations, and the effect of the coupling reduces the bias in the background skin temperature by ~ 1 K While diurnal bias correction does not improve the mean temperature much over daily, but the amplitude is generally improved Having coordinated flux stations at many different climate regimes greatly improves the validation of the surface energy budgets

Future Work Long term assimilation desired for CEOP EOP3 and EOP4 The degradation of latent heat flux was ~10Wm-2 at two CEOP stations, currently looking at the relationships between Ts bias and soil moisture bias (nonlinear and less than ideal) There are ongoing experiments in the GMAO to assimilate clouds and also soil moisture, a multi-variate assimilation would be more desirable ISCCP presently does not extend past Sept 2001, MODIS is available for Aqua and Terra, but only 4 times/day